Open access peer-reviewed Edited Volume

Introduction to Data Science and Machine Learning

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10,240 Chapter Downloads

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Academic Editor

Keshav Sud

University of Illinois at Chicago

Co-editors

Pakize Erdogmus

Duzce University

Seifedine Kadry

Beirut Arab University

PublishedMarch 25th, 2020

Doi10.5772/intechopen.77469

ISBN978-1-83880-334-6

Print ISBN978-1-83880-333-9

eBook (PDF) ISBN978-1-83880-371-1

Copyright year2020

Number of pages232

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Edited Volume and chapters are indexed in

  • Google Scholar
  • DOAB
  • Crossref
  • Dimension
  • OpenAIRE
  • AZ ebsco
  • Worldcat
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Table of Contents

Open access  chapters

3. Software Design for Success

By Laura M. Castro

593
4. Embedded Systems Based on Open Source Platforms

By Zlatko Bundalo and Dusanka Bundalo

956
2
5. The K-Means Algorithm Evolution

By Joaquín Pérez-Ortega, Nelva Nely Almanza-Ortega, Andrea Vega-Villalobos, Rodolfo Pazos-Rangel, Crispín Zavala-Díaz and Alicia Martínez-Rebollar

1,077
4
693
9. The Software to the Soft Target Assessment

By Lucia Mrazkova Duricova, Martin Hromada and Jan Mrazek

769
10. The Methodological Standard to the Assessment of the Traffic Simulation in Real Time

By Jan Mrazek, Martin Hromada and Lucia Duricova Mrazkova

751
12. Serialization in Object-Oriented Programming Languages

By Konrad Grochowski, Michał Breiter and Robert Nowak

1,094

IMPACT OF THIS BOOK AND ITS CHAPTERS

10,240 Total Chapter Downloads

7 Crossref Citations

2 Web of Science Citations

17 Dimensions Citations

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